Butterfly Community Diversity in the Qinling Mountains

The Qinling Mountains are one of the oldest mountain ranges in China and a global biodiversity research and conservation hotspot. However, there is a lack of systematic research and survey of butterfly diversity in this region. Based on the butterfly taxa, combined with the changes in natural climate, altitude gradient and season in the Qinling Mountains, the butterfly diversity and community structure changes in 12 counties in the middle Qinling Mountains were analyzed by transect surveys and platform data analyses. A total of 9626 butterflies were observed, belonging to 427 species across 175 genera and 5 families. The species richness on the southern slope of the Qinling Mountains was higher than on the northern slope. We also studied the variation in alpha and beta diversity of butterflies. The results show that butterfly species were abundant and the highest diversity was found at the middle altitudes (1000–2000 m). Moreover, there were obvious seasonal differences in both species and number of butterflies. The community similarity in spring, summer and autumn was low, with limited species co-existing. The butterflies in the Qinling Mountains reserve area were the most abundant, exhibiting no significant difference with those in the ecotone and the farm area. Finally, we did an assessment of butterflies as endangered and protected species. In conclusion, our long-term butterfly survey data show that human disturbance and climate and environmental changes jointly shape the butterfly diversity in the middle of the Qinling Mountains.

Attribution Analysis of Runoff Variation in the Yue River Watershed of the Qinling Mountains

In recent decades, global climate change, especially human activities, has led to profound changes in the hydrological cycle and hydrological processes in watersheds. Taking the Yue River watershed in the Qinling Mountains in China as the study area, the Mann–Kendall test and Pettitt mutation test method were used to analyze the various characteristics of hydrological and climatic elements from 1960 to 2018. Then, the elastic coefficient method based on the Budyko framework was used to estimate the elastic coefficient of runoff change on each influencing factor. The results showed that the annual runoff decreased at a rate of 0.038 × 108 m3/a ( P > 0.05 ), and a significant abrupt change occurred in 1990. The annual precipitation and potential evapotranspiration (ET0) increased and decreased, with change rates of 0.614 mm/a and −0.811 mm/a ( P > 0.05 ), respectively. The elasticity coefficients of precipitation, ET0, and the underlying surface were 1.95, −0.95, and −0.85, respectively, indicating that annual runoff was most sensitive to the change in precipitation, followed by the change in ET0, and had the lowest sensitivity to the change in the underlying surface. Underlying surface change is the main factor of runoff decrease; the contribution is 89.07%. The total contribution of climate change to runoff change is 10.93%, in which the contributions of precipitation and ET0 are 17.59% and −6.66%, respectively. The NDVI reflecting underlying surface change has been increasing since 1990, which is an important reason for the runoff decrease.

Terrain Effects on Regional Precipitation in a Warm Season over Qinling-Daba Mountains in Central China

The terrain effects of Qinling–Daba Mountains on reginal precipitation during a warm season were investigated in a two-month day-to-day experiment using the Weather Research and Forecasting (WRF) model. According to the results from the terrain sensitivity experiment with lowered mountains, Qinling–Daba Mountains have been found to have an obvious effect on both the spatial-temporal distribution and diurnal cycle of reginal precipitation from July to August in 2019, where the Qinling Mountains mainly enhanced the precipitation around 34° N, and the Daba Mountains mainly enhanced it around 32° N at the time period of early morning and midnight. Horizontal distribution of water vapor and convective available potential energy (CAPE), as well as cross section of vertical velocity of wind and potential temperature has been studied to examine the key mechanisms for these two mountains’ effect. The existence of Qinling Mountains intercepted transportation of water vapor from South to North in the lower troposphere to across 34° N and caused an obvious enhancement of CAPE in the neighborhood, while the Daba Mountains intercepted the northward water vapor transportation to across 32° N and caused an enhanced CAPE nearby. The time period of the influence is in a good accordance with the diurnal cycle. In the cross-section, the existence of Qinling Mountains and Daba Mountains are found to stimulate the upward motion and unstable environment effectively at around 34° N and 32° N, separately. As a result, the existence of the two mountains lead to a favorable environment in water vapor, thermodynamic, and dynamic conditions for this warm season precipitation.

Dynamic Responses of Multidiameter-class Fine Roots at Different Soil Depths to Thinning Measures in a Secondary Forest in China

Background: Fine roots make critical contributions to carbon stocks and terrestrial productivity, and multidiameter-class fine roots exhibit functional heterogeneity. However, the dynamic characteristics of multidiameter-class fine roots at different soil depths following thinning disturbances are poorly understood. We investigated the biomass, production, mortality and turnover rate of < 0.5 mm, 0.5–1 mm and 1–2 mm fine roots at 0-20 cm, 20-40 cm and 40-60 cm soil depths under five thinning intensities (0%, 15%, 30%, 45%, and 60%) in a secondary forest in the Qinling Mountains. Results: The biomass, production and turnover rate of < 0.5 mm fine roots fluctuated with increasing thinning intensity, while 0.5-1 mm and 1-2 mm fine root biomass significantly decreased. Thinning measures had no effects on fine root necromass (except for T4) or mortality. The fine root dynamic characteristics in deeper soils were more sensitive to thinning measures. Principal component analysis results show that increased < 0.5 mm fine root biomass and production resulted from increased shrub and herb diversity and biomass and decreased soil nutrient availability, stand volume and litter biomass, whereas 0.5-1 mm and 1-2 mm fine root biomass showed the opposite trends and change mechanisms. Conclusions: Our results provide evidence of the positive effect of thinning on very fine root (< 0.5 mm) biomass and production and the negative effect on thicker fine roots (0.5-1, 1-2 mm) or all fine root (< 2 mm) biomass. From the perspective of fine root biomass and productivity, T2 (30%) is recommended for use in secondary forests of the Qinling Mountains. Moreover, our results suggest that thinning practices have varied effects on the dynamic characteristics of multidiameter-class fine roots.

Quantitative Assessment of the Contributions of Climate Change and Human Activities to Vegetation Variation in the Qinling Mountains

Quantitative assessment of the contributions of climate change and human activities to vegetation change is important for ecosystem planning and management. To reveal spatial differences in the driving mechanisms of vegetation change in the Qinling Mountains, the changing patterns of the normalized difference vegetation index (NDVI) in the Qinling Mountains during 2000–2019 were investigated through trend analysis and multiple regression residuals analysis. The relative contributions of climate change and human activities on vegetation NDVI change were also quantified. The NDVI shows a significant increasing trend (0.23/10a) from 2000 to 2019 in the Qinling Mountains. The percentage of areas with increasing and decreasing trends in NDVI is 87.96% and 12.04% of the study area, respectively. The vegetation change in the Qinling Mountains is caused by a combination of climate change and human activities. The Tongguan Shiquan line is a clear dividing line in the spatial distribution of drivers of vegetation change. Regarding the vegetation improvement, the contribution of climate change and human activities to NDVI increase is 51.75% and 48.25%, respectively. In the degraded vegetation area, the contributions of climate change and human activities to the decrease in NDVI were 22.11% and 77.89%, respectively. Thus, vegetation degradation is mainly caused by human activities. The implementation of policies, such as returning farmland to forest and grass, has an important role in vegetation protection. It is suggested that further attention should be paid to the role of human activities in vegetation degradation when formulating corresponding vegetation protection measures and policies.